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<p>Power quality has prominently gained its importance in power systems with the advancement of technology. Voltage sags/swells, harmonics, and other disturbances are the major issues causing most of the technical and financial damages which are reducing the quality of energy supplied. To overcome these challenges design of a unified power quality conditioner (UPQC) plays a vital role in mitigating the PQ issues. In this paper, an advanced neural network base approach is developed to manage UPQC to maintain a constant power supply for the end users. DC link of UPQC is taken from PV, fuel, and battery at a specific range. The compensator DC link is linked in a smart grid with nonlinear load. On the other hand, the switching pulse was performed with the use of the Gated Recurrent Unit (GRU) controller technique. Various fault conditions are created to make a dataset that is utilized to design the GRU that analyses the load voltage and current at each second to generate a pulse for UPQC. The performance is evaluated utilizing an advanced controller under various conditions, including swell, sag, harmonics, and combined three-phase faults. The low harmonic content of voltage is 0.04%, 0.25%, and 0.98%. The suggested controller is accessible with 99.5% specificity, 99% sensitivity, and 98% accuracy. The proposed controller provides low harmonic content while operating in a highly secure, dependable, and efficient manner.</p>

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GRU controller-based UPQC compensator design for improving power quality in grid-integrated non-linear load system

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月4日

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  • B. Srikanth Goud,
  • Ch. Naga Sai Kalyan,
  • Gundala Srinivasa Rao,
  • Bhabasis Mohapatra,
  • Narsimha Reddy Kuppireddy,
  • Harish Pulluri,
  • Ch. Rami Reddy,
  • Mohammad Shorfuzzaman,
  • Basem Abu Zneid,
  • Mukesh Pushkarna

摘要

Power quality has prominently gained its importance in power systems with the advancement of technology. Voltage sags/swells, harmonics, and other disturbances are the major issues causing most of the technical and financial damages which are reducing the quality of energy supplied. To overcome these challenges design of a unified power quality conditioner (UPQC) plays a vital role in mitigating the PQ issues. In this paper, an advanced neural network base approach is developed to manage UPQC to maintain a constant power supply for the end users. DC link of UPQC is taken from PV, fuel, and battery at a specific range. The compensator DC link is linked in a smart grid with nonlinear load. On the other hand, the switching pulse was performed with the use of the Gated Recurrent Unit (GRU) controller technique. Various fault conditions are created to make a dataset that is utilized to design the GRU that analyses the load voltage and current at each second to generate a pulse for UPQC. The performance is evaluated utilizing an advanced controller under various conditions, including swell, sag, harmonics, and combined three-phase faults. The low harmonic content of voltage is 0.04%, 0.25%, and 0.98%. The suggested controller is accessible with 99.5% specificity, 99% sensitivity, and 98% accuracy. The proposed controller provides low harmonic content while operating in a highly secure, dependable, and efficient manner.